DOES POPULATION DENSITY AND HUMAN ACTIVITIES AFFECT THE RATE OF REDUCTION OF FUKUSHIMA DAICHI RADIATIONS

This study uses Nihommatsu city and Mimanisoma City as case studies. The two cities are 70km and 30km from Fukushima Daichi Plant respectively.

Part I: Nihomatsu City,70km to Fukushima Daichi

NB:Important Notes from the Nuclear Regulation Authority onJAEA website Purposes of this vehicle survey were: 1. To ascertain the tendency and cause of time change of air dose rates by comparing past vehicle survey data and survey meter data at the height of 1 m above ground as well as “walk survey” data, and 2. To contribute to the establishment of radioactive substances distribution prediction model. MEXT evaluated the decrease in the air dose rates caused by the decay of cesium during the survey period and it was around 1%, which was smaller than the errors of measuring instruments source

Loading June 2011 Fukushima Data and selecting Nihomatsu’s.

Change to machine readeable column names

names(niho) <- c("gridcode","pref","city","gridCenterNorthlat","gridCenterEastlng","gridCenterNorthlatDec",
                 "gridCenterEastlngDec","daichi_distance","no_samples","AvgAirDoseRate",
                       "NE_nLat","NE_eLong","NW_nLat","NW_eLong",
                       "SW_nLat","SW_eLong","SE_nLat","SE_eLong")
names(niho2013) <- c("gridcode","pref","city","gridCenterNorthlat","gridCenterEastlng","gridCenterNorthlatDec",
                     "gridCenterEastlngDec","daichi_distance","no_samples","AvgAirDoseRate",
                     "NE_nLat","NE_eLong","NW_nLat","NW_eLong",
                     "SW_nLat","SW_eLong","SE_nLat","SE_eLong")
#Strip Nihommatsu city,
niho$city[niho$city == "Nihommatsu city"] <- "nihommatsu"
niho2013$city[niho2013$city == "Nihommatsu city"] <- "nihommatsu"

filter nihomatsu dataset

Create air dose quantiles that are plot-able,6 categorical variables.

Visible reduction of Average Air Dose Distribution by half in Nihomatsu. Trouble is knowing the distribution of causes of this reduction?

plot(nihom2013$AvgAirDoseRate,niho_q$AvgAirDoseRate)

Color function

iro <- colorFactor(
        palette = "YlOrRd",
        domain = niho_q$dose_quants
)
iro2013 <- colorFactor(
        palette = "YlOrRd",
        domain = nihom2013_q$dose_quants
)
# Link of Daichi
fukulink <- paste(sep = "<br/>",
                  "<br><a href='http://www.tepco.co.jp/en/decommision/index-e.html'>Fukushima Daichi</a></b>",
                  "Source of radiations"
)

Nihomatsu Average Air Dose Rate for 2011

niho_plot <- leaflet() %>%
        addTiles()%>%
        addRectangles(data = niho_q,lng1 = ~SW_eLong, lat1 = ~SW_nLat,lng2 = ~NE_eLong, lat2 = ~NE_nLat,
                      color = ~iro(niho_q$dose_quants))%>%
        addLegend("bottomright", pal = iro, values = niho_q$dose_quants,
                  title = "AvgAirDoseRates",
                  labFormat = labelFormat(prefix = "µSv/h "),
                  opacity = 1)%>%
        addPopups(lat = 37.4211, lng = 141.0328,popup = fukulink,
                  options = popupOptions(closeButton = TRUE)) 
niho_plot

Nihomatsu Average Air Dose Rate for 2013

niho2013_plot <- leaflet() %>%
        addTiles()%>%
        addRectangles(data = nihom2013_q,lng1 = ~SW_eLong, lat1 = ~SW_nLat,lng2 = ~NE_eLong, lat2 = ~NE_nLat,
                      color = ~iro2013(nihom2013_q$dose_quants))%>%
        addLegend("bottomright", pal = iro2013, values = nihom2013_q$dose_quants,
                  title = "AvgAirDoseRates",
                  labFormat = labelFormat(prefix = "µSv/h "),
                  opacity = 1)%>%
        addPopups(lat = 37.4211, lng = 141.0328,popup = fukulink,
                  options = popupOptions(closeButton = TRUE)) 
niho2013_plot

Plot Nihomatsu geo locations to Average Air Dose

ggplot(niho_q, aes(daichi_distance,AvgAirDoseRate)) +
        geom_point() +
        geom_smooth(se = FALSE)+
        ggtitle("AvgAirDose against Distance to Daichi Plant")

Repeat above visualization from a different view

ggplot(data = niho_q) +
        geom_bar(mapping = aes(x = daichi_distance, fill = dose_quants), width = 1)+
        ggtitle("AvgAirDose Measured Counts against Daichi Distance")

PART II: Minamisoma City, 30km to Fukushima Daichi

mina <- read_csv("niho.csv")
dim(mina)
## [1] 45273    18
# View(mina)
#Select Minamisoma City only
mina$city[mina$city == "Minamisoma city"] <- "minamisoma"
#filter nihomatsu observations only
mina <- subset(mina, city == "minamisoma")
dim(mina)
## [1] 1985   18
summary(mina$AvgAirDoseRate)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.210   0.520   0.780   1.771   1.800  18.000
#plot(mina$AvgAirDoseRate)

Create air dose quantiles that are plot-able,6 categorical variables.

mina_q <- mina %>%
        mutate(mina_quants = cut2(mina$AvgAirDoseRate,cuts=seq(0.2,20,2.2),levels.mean=TRUE))
## View(mina_q)
mina_q <- na.omit(mina_q)
write_csv(mina_q, path = "mina_q.csv")

Color function

mina_iro <- colorFactor(
        palette = "Set1",
        domain = mina_q$mina_quants
)

Minamisoma Average Air Dose Rate for 2011

mina_plot <- leaflet() %>%
        addTiles()%>%
        addRectangles(data = mina_q,lng1 = ~SW_eLong, lat1 = ~SW_nLat,lng2 = ~NE_eLong, lat2 = ~NE_nLat,
                      color = ~mina_iro(mina_q$mina_quants))%>%
        addLegend("bottomright", pal = mina_iro, values = mina_q$mina_quants,
                  title = "AvgAirDoseRates",
                  labFormat = labelFormat(prefix = "µSv/h "),
                  opacity = 1)%>%
        addPopups(lat = 37.4211, lng = 141.0328,popup = fukulink,
                  options = popupOptions(closeButton = TRUE)) 
mina_plot

Minamisoma AvgAirDose against Distance to Daichi Plant

ggplot(mina_q, aes(daichi_distance,AvgAirDoseRate)) +
        geom_point() +
        geom_smooth(se = FALSE)+
        ggtitle("AvgAirDose against Distance to Daichi Plant")

Minamisoma AvgAirDose Measured Counts against Daichi Distance

ggplot(data = mina_q) +
        geom_bar(mapping = aes(x = daichi_distance, fill = mina_quants), width = 1)+
        ggtitle("AvgAirDose Measured Counts against Daichi Distance")

to be continued